1. Introduction
The present invention relates to a noise reduction apparatus which is mounted on a household VTR or the like.
2. Description of the Related Art
Recently, a noise reduction apparatus for reducing noise in playing is being mounted on a household VTR or the like. A signal processing method of a conventional noise reduction apparatus is elucidated hereafter.
The conventional noise reduction apparatus is based on the fact that the noise is noncorrelative, whereas a video signal has a strong correlation between fields or frames. Noise reduction is attempted by deriving a weighted mean with respect to the signal of the previous one field or frame.
A general configuration of a noise reduction apparatus of a field recursive type is represented by the following equation. EQU Y.sub.n =(1-k)x.sub.n +ky.sub.n-1 =x.sub.n -k(x.sub.n -y.sub.n-1)(1),
where: 0.ltoreq.k.ltoreq.1
x.sub.n : input signal
y.sub.n-1 : field memory output signal
Y.sub.n : output signal.
As is understood from the equation (1), a process which derives a weighted mean of two fields is equivalent to a process where a difference signal (hereinafter referred to as a field difference signal) between the two fields is multiplied by a constant and then subtracted from the input signal.
Hereafter, the multiplication process of k and the field difference signal (x.sub.n -y.sub.n-1) in the equation (1) is elucidated.
In the equation (1), in the field difference signal (x.sub.n -y.sub.n-1), noise has been extracted in a still picture part and a signal in a moving picture part, respectively.
With respect to the field difference signal, a small amplitude is regarded as noise, and a subtractive quantity from the input signal is increased by bringing the valve of k close to 1.
Moreover, as the amplitude becomes larger, this is regarded as variation of the signal, and k is close to 0. A nonlinear process is applied so as to decrease the subtractive quantity from the input signal.
This is based on a fact that in general the amplitude of the noise is smaller in comparison with that of the signal, and the result k(x.sub.n -y.sub.n-1) of the nonlinear operation can be regarded as extracted noise.
However, in the noise reduction apparatus of the above constitution, since the above operation is individually performed for each pixel, the signal or the noise is difficult to distinguish with respect to a little movement, and an afterimage tends to be produced.
In contrast with this, there is a proposal of a noise reduction apparatus wherein Hadamard transformation, one of orthogonal transformations, is applied to the field or the frame difference signal and extraction of the feature of a picture is performed. In this apparatus, separation of the noise is made relatively easy (for example, The Journal of Institute of Television Engineers of Japan, Vol. 37, No. 12, 1983).
The principle of this kind of a noise reduction apparatus is briefly elucidated.
A signal block is formed by extracting four data in horizontal direction, two in vertical direction, i.e. eight data in total from the field or the frame difference signal derived by subtracting the output of a field or a frame memory from an input video signal. The Hadamard transformation of 2.times.4 dimension is then applied. The Hadamard transformation is a kind of frequency conversion, and each data in the above-mentioned block is separated into eight spatial frequency components.
With respect to each transformed component derived by the Hadamard transformation, the above-mentioned nonlinear operation is applied and a noise component is extracted. This is returned to the eight data by Hadamard inverse transformation, and is made into noise. The noise is extracted from each data of the difference signal of the field or the frame in the original block and is subtracted from the input signal to carry out the noise reduction.
Since the signal which is included in each data in the signal block is considered to have a specific frequency component, the signal concentrates at some of transformation component by applying the Hadamard transformation. In contrast, the frequency component of the noise is considered to be random, and is divided equally into each component.
Therefore, in the transformed component where the signal does not concentrate, only the noise can be extracted. In the transformed component where the signal concentrates, a level difference of the signal and the noise increases and a rate of the signal which is included in the extracted noise decreases. For this reason, the noise reduction apparatus wherein occurrence of afterimage is reduced can be constituted.
However, in the conventional noise reduction apparatus as mentioned above, if a signal block is taken so that the data does not overlap, discontinuity of data, so-called block distortion is absolutely susceptible to occurrence at the boundary of the block.
Moreover, if the transformation is performed so that a part of the data overlaps between the signal blocks, though the block distortion is alleviated, an after process so as to average among data is required since the inversely transformed data also overlaps, and the apparatus circuit scale increases.
Furthermore, since two data are required in the vertical direction in order to constitute a block, a 1H (H: horizontal scanning period) delay element is required before a Hadamard transformation device and after a Hadamard inverse-transformation device. Moreover, in order to coincide a timing of an extracted noise derived by the Hadamard inverse-transformation device and an input video signal, another 1H delay element is required. This also causes increase in the circuit scale.